An exploratory study of quality circles and team building in two hospital settings

Typescript.Thesis (D.P.H.)--University of Hawaii at Manoa, 1984.Bibliography: leaves [171]-177.Photocopy.xi, 177 leaves bound ill. 29 c

Glyphosate, Hard Water and Nephrotoxic Metals: Are They the Culprits Behind the Epidemic of Chronic Kidney Disease of Unknown Etiology in Sri Lanka?

The current chronic kidney disease epidemic, the major health issue in the rice paddy farming areas in Sri Lanka has been the subject of many scientific and political debates over the last decade. Although there is no agreement among scientists about the etiology of the disease, a majority of them has concluded that this is a toxic nephropathy. None of the hypotheses put forward so far could explain coherently the totality of clinical, biochemical, histopathological findings, and the unique geographical distribution of the disease and its appearance in the mid-1990s. A strong association between the consumption of hard water and the occurrence of this special kidney disease has been observed, but the relationship has not been explained consistently. Here, we have hypothesized the association of using glyphosate, the most widely used herbicide in the disease endemic area and its unique metal chelating properties. The possible role played by glyphosate-metal complexes in this epidemic has not been given any serious consideration by investigators for the last two decades. Furthermore, it may explain similar kidney disease epidemics observed in Andra Pradesh (India) and Central America. Although glyphosate alone does not cause an epidemic of chronic kidney disease, it seems to have acquired the ability to destroy the renal tissues of thousands of farmers when it forms complexes with a localized geo environmental factor (hardness) and nephrotoxic metals

A Population-Based Study Investigating the Association between Metabolic Syndrome and Hepatitis B/C Infection (Keelung Community-Based Integrated Screening Study No. 10)

Objectives: We aimed to assess the association between metabolic syndrome (MS) and hepatitis B/C virus infection using a large population-based study. Design and methods: A population-based cross-sectional study design was adopted with a total of 53 528 subjects being enrolled from the integrated multiple diseases screening program in Keelung, Taiwan. Evidence of past hepatitis B/C infection, acquired during childhood or as a young adult, was identified during the two-stage liver cancer screening part of the process. Information on biochemical markers and anthropometric measures related to MS, such as fasting blood sugar, triglyceride and high-density lipoprotein (HDL), abdominal circumference and blood pressure (BP), were collected routinely while screening for hypertension, type 2 diabetes, and hyperlipidemia. Logistic regression was used to estimate odds ratios and related 95% confidence intervals for the associations between MS and hepatitis B/C infection. Results: High blood pressure (SBP >= 135mmHg or DBP >= 85 mmHg) (adjusted odd ratio: 0.89 (0.83-0.94)) and high triglyceride (>= 150 mg/dl) (adjusted odds ratio: 0.65 (0.60 -0.69)) were, after adjusting for gender and age, inversely associated with being HBsAg positive (P < 0.05). The likelihood of developing MS was lower in the HBsAg positive than the HBsAg negative (adjusted odds ratio: 0.84 (0. 76-0. 93)). A positive association between being anti-HCV positive and having low serum HDL (male < 40 mg/dl, female < 50 mg/ dl) was also noted (adjusted odds ratio: 1.61 (1.37-1.88) after controlling for gender and age). High triglyceride was inversely associated with being anti-HCV positive (adjusted odds ratio: 0.63 (0.55-0.71). Conclusions: There is an inverse association between MS and hepatitis B virus infection whereas the association was heterogeneous for HCV infection with a positive association with abnormal serum HDL but an inverse association with hypertriglyceridemia

Stereo vision combined with laser profiling for mapping of pipeline internal defects

Underground potable water pipes are essential infrastructure assets for any country. A significant proportion of those assets are deteriorating due to pipe corrosion which results in premature failure of pipes causing enormous disruptions to the public and loss to the economy. To address such adverse effects, the water utilities in Australia exploit advanced pipelining technologies with a motive of extending the service life of their pipe assets. However, the linings are prone to defects due to improper liner application and unfavorable environmental conditions during the liner curing phase. To monitor the imperfections of the pipe linings, in this article, we propose a mobile robotic sensing system that can scan, detect, locate and measure pipeline internal defects by generating three-dimensional RGB-Depth maps using stereo camera vision combined with infrared laser profiling unit. The system does not require complex calibration procedures and it utilizes orientation correction to provide accurate real-time RGB-D maps. The defects are identified and color mapped for easier visualization. The robotic sensing system was extensively tested in laboratory conditions followed by field deployments in buried water pipes in Sydney, Australia. The experimental results show that the RGB-D maps were generated with millimeter (mm) level accuracy with demonstrated liner defect quantification

Using UHF-RFID signals for robot localization inside pipelines

Underground water pipes are important to any country's infrastructure. Overtime, the metallic pipes are prone to corrosion, which can lead to water leakage and pipe bursts. In order to prolong the service life of those assets, water utilities in Australia apply protective pipe linings. Long-term monitoring and timely intervention are crucial for maintaining those lining assets. However, the water utilities do not possess the comprehensive technology to achieve it. The main reasons for lacking such technology are the unavailability of sensors and accurate robot localization technologies. Feature based localization methods such as SLAM has limited use as the application of liners alters the features and the environment. Encoder based localization is not accurate enough to observe the evolution of defects over a long period of time requiring unique defect correspondence. This motivates us to explore accurate contact-less and wireless based localization methods. We propose a cost-effective localization method using UHF-RFID signals for robot localization inside pipelines based on Gaussian process combined particle filter. Experiments carried out in field extracted pipe samples from the Sydney water pipe network show that using the RSSI and Phase data together in the measurement model with particle filter algorithm improves the localization accuracy up to 15 centimeters precision

Stereo vision combined with laser profiling for mapping of pipeline internal defects

Underground potable water pipes are essential infrastructure assets for any country. A significant proportion of those assets are deteriorating due to pipe corrosion which results in premature failure of pipes causing enormous disruptions to the public and loss to the economy. To address such adverse effects, the water utilities in Australia exploit advanced pipelining technologies with a motive of extending the service life of their pipe assets. However, the linings are prone to defects due to improper liner application and unfavorable environmental conditions during the liner curing phase. To monitor the imperfections of the pipe linings, in this article, we propose a mobile robotic sensing system that can scan, detect, locate and measure pipeline internal defects by generating three-dimensional RGB-Depth maps using stereo camera vision combined with infrared laser profiling unit. The system does not require complex calibration procedures and it utilizes orientation correction to provide accurate real-time RGB-D maps. The defects are identified and color mapped for easier visualization. The robotic sensing system was extensively tested in laboratory conditions followed by field deployments in buried water pipes in Sydney, Australia. The experimental results show that the RGB-D maps were generated with millimeter (mm) level accuracy with demonstrated liner defect quantification

Assistant Editors

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